kangar00: Kernel Approaches for Nonlinear Genetic Association Regression (original) (raw)

Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel).

Version: 1.4.2
Depends: R (≥ 3.5.0)
Imports: methods, bigmemory, sqldf, CompQuadForm, data.table, lattice, igraph
Suggests: biomaRt, KEGGgraph, testthat
Published: 2024-05-09
DOI: 10.32614/CRAN.package.kangar00
Author: Juliane Manitz [aut, cre], Benjamin Hofner [aut], Stefanie Friedrichs [aut], Patricia Burger [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb], Heike Bickeboeller [ctb]
Maintainer: Juliane Manitz
BugReports: https://github.com/jmanitz/kangar00/issues
License: GPL-2
URL: https://kangar00.manitz.org/
NeedsCompilation: no
Citation: kangar00 citation info
CRAN checks: kangar00 results

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